lab4

SNPs<- read.table("23andMe_complete.txt", header = TRUE, sep = "\t")

library(plotly)

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library(tidyverse)

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library(DT)

library(ggplot2)

#exercise 1
ggplot(data = SNPs) +
  geom_bar( mapping = aes(x = chromosome), fill = "blue") +
  ggtitle("Total SNPs for each chromosome") +
  ylab("Total number of SNPs") +
  xlab("Chromosome") 

#exercise 2
mycolor<-c("AA"="red","AC"="red","AG"="red","AT"="red","CC"="red","CG"="red","CT"="red","DD"="blue","DI"="blue","D"="blue","I"="blue","II"="blue","GG"="red","GT"="red","TT"="red","A"="yellow","C"="yellow","G"="yellow","T"="yellow","--" = "magenta")
p <- ggplot(SNPs, aes(x = chromosome, fill = genotype)) 
p <- p + geom_bar() +
  ggtitle("Total SNPs for each chromosome") +
  ylab("Genotype Count") +
  xlab("Chromosome Numbers") +
  scale_fill_manual(values=c(mycolor))
p 

#exercise 3

Total SNPs for each chromosome

#exercise 4

Total SNPs for each chromosome

#exercise 5
ggplotly(
  ggplot(data = SNPs) +
    geom_bar(mapping = aes(x = chromosome, fill = genotype)) +
    facet_wrap(~ genotype, ncol = 3, nrow = 15, scales = "fixed") +
    theme(axis.text.x = element_text( size = 3),) +
    theme(axis.text = element_text( size = 5),) +
    ggtitle("Total SNPs for each chromosome") +
    ylab("Genotype Count") +
    xlab("Chromosome Numbers") 
)

#exercise 6
R <- subset(SNPs, chromosome == "Y" )
datatable(R) 

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